Autonomous development of two-phase cooling architecture

ABSTRACT

Techniques for autonomously modeling a two-phase cooling architecture are provided. In one example, a computer-implemented method can comprise generating, by a system operatively coupled to a processor, a reduced physics model based on a profile of a heat source and a parameter of a cooling structure. The reduced physics model can provide an output. Also, the computer-implemented method can comprise generating, by the system, a full physics model based on the output. The computer-implemented method can further comprise combining, by the system, the reduced physics model and the full physics model to define an architecture that achieves a flow distribution of a coolant.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

This invention was made with Government support under Contract No.:FA8650-14-C-7466 awarded by Defense Advanced Research Projects Agency(DARPA). The Government has certain rights in this invention.

BACKGROUND

The subject disclosure relates to designing a cooling structure, andmore specifically, to generating models that define an architecture fortwo-phase cooling.

SUMMARY

The following presents a summary to provide a basic understanding of oneor more embodiments of the invention. This summary is not intended toidentify key or critical elements, or delineate any scope of theparticular embodiments or any scope of the claims. Its sole purpose isto present concepts in a simplified form as a prelude to the moredetailed description that is presented later. In one or more embodimentsdescribed herein, systems, computer-implemented methods, apparatusesand/or computer program products that can facilitate modeling a twophase cooling structure are described.

According to an embodiment, a computer-implemented method is provided.The computer-implemented method can comprise generating, by a systemoperatively coupled to a processor, a reduced physics model based on aprofile of a heat source and a parameter of a cooling structure. Thereduced physics model can provide an output. The computer-implementedmethod can also comprise generating, by the system, a full physics modelbased on the output. Also, the computer-implemented method can comprisecombining, by the system, the reduced physics model and the full physicsmodel to define an architecture that can achieve a flow distribution ofa coolant.

According to another embodiment, a computer program product is provided.The computer program product can facilitate a design of two-phasecooling structures. The computer program product can comprise a computerreadable storage medium that can have program instructions embodiedtherewith. The program instructions can be executed by a processor tocause the processor to generate a reduced physics model based on aprofile of a heat source and a parameter of a cooling structure. Thereduced physics model can provide an output. Further, the programinstructions can be executed by a processor to cause the processor togenerate a full physics model based on the output. Also, the programinstructions can be executed by a processor to cause the processor tocombine the reduced physics model and the full physics model to definean architecture that can achieve a flow distribution of a coolant.

According to another embodiment, a system is provided. The system cancomprise a memory that can store computer executable components. Thesystem can also comprise a processor that can execute the computerexecutable components stored in the memory. The computer executablecomponents can comprise a reduced physics model component that cangenerate a reduced physics model based on a profile of a heat source anda parameter of a cooling structure. The reduced physics model canprovide an output. Also, the computer executable components can comprisea full physics model component that can generate a full physics modelbased on the output. Further, the computer executable components cancomprise a combination component that can combine the reduced physicsmodel and the full physics model to define an architecture that canachieve a flow distribution of a coolant.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a block diagram of an example, non-limiting systemthat can facilitate modeling a two-phase cooling structure in accordancewith one or more embodiments described herein.

FIG. 2 illustrates a diagram of an example, non-limiting reduced physicsmodel that can be generated in accordance with one or more embodimentsdescribed herein.

FIG. 3 illustrates a diagram of an example, non-limiting full physicsmodel that can be generated in accordance with one or more embodimentsdescribed herein.

FIG. 4 illustrates a flow chart of an example, non-limiting method thatcan facilitate modeling a two-phase cooling structure in accordance withone or more embodiments described herein.

FIG. 5 illustrates a block diagram of another example, non-limitingsystem that can facilitate modeling a two-phase cooling structure inaccordance with one or more embodiments described herein.

FIG. 6 illustrates a flow chart of another example, non-limiting methodthat can facilitate modeling a two-phase cooling structure in accordancewith one or more embodiments described herein.

FIG. 7 illustrates a block diagram of another example, non-limitingsystem that can facilitate modeling a two-phase cooling structure inaccordance with one or more embodiments described herein.

FIG. 8 illustrates a flow chart of an example, non-limitingcomputer-implemented method that can facilitate modeling a two-phasecooling structure in accordance with one or more embodiments describedherein.

FIG. 9 illustrates a flow chart of another example, non-limitingcomputer-implemented method that can facilitate modeling a two-phasecooling structure in accordance with one or more embodiments describedherein.

FIG. 10 illustrates a block diagram of an example, non-limitingoperating environment in which one or more embodiments described hereincan be facilitated.

DETAILED DESCRIPTION

The following detailed description is merely illustrative and is notintended to limit embodiments and/or application or uses of embodiments.Furthermore, there is no intention to be bound by any expressed orimplied information presented in the preceding Background or Summarysections, or in the Detailed Description section.

One or more embodiments are now described with reference to thedrawings, wherein like referenced numerals are used to refer to likeelements throughout. In the following description, for purposes ofexplanation, numerous specific details are set forth in order to providea more thorough understanding of the one or more embodiments. It isevident, however, in various cases, that the one or more embodiments canbe practiced without these specific details.

Three dimensional (3D) integration of microelectronic chips into stacksis an enabling technology to provide a path for increasing computationalperformance. Conventional single chip cooling solutions that utilizeheat sinks or cold-plates thermally coupled to the backside of adie-package cannot provide sufficient cooling for high power 3D chipstacks. To provide sufficient cooling, embedded liquid coolingarchitecture can be utilized, wherein a liquid coolant can be passedbetween the layers of stacked chips. However, such embedded liquidcooling can add a new set of constraints to the chip system (e.g., theavailable micron-scale cavity dimensions, working fluid, and/oroperating pressures). For example, cavity heights can be limited byfabrication processes and the performance of electrical links betweenchips in the stack, which include through silicon vias (TSVs) betweenand through the layers of stacked chips. Also, a significant amount ofpressure drop can be observed when a nominal amount of coolant (e.g.water) flow rate is pumped through embedded micro-channels of usableheight and width. In addition, significant integrated heat load alongthe length (e.g., about 10 millimeters) of a processor die can cause alarge temperature gradient across the channel. Moreover, the use ofwater as coolant can require isolation from power and signalinterconnects and can cause high frequency signal transmission losses.

Given the conditions of embedded liquid cooling, some liquid coolingtechniques utilize two-phase liquid cooling, wherein a chip-to-chipinterconnect-compatible dielectric fluid is converted from liquid tovapor phase as it flows through embedded micron-scale cavities. Thecooling can be achieved by utilizing the latent heat of vaporization ofthe dielectric coolant whereby, large amounts of heat can be removedwith low coolant flow rates and small changes in coolant and chiptemperatures across the coolant cavity/channel. Such chip-integratedmicrometer scale two-phase cooling technology can be essential to fullyoptimize the benefits of improved integration density and modularity of3D stacking of high performance integrated circuits (ICs). However,two-phase cooling architecture can have significant developmentalchallenges. One such challenge is to develop a high fidelity thermalmodel of a microprocessor having spatially varying heat sources togetherwith a two-phase microfluidic convection network. The fundamentalchallenge is to integrate together the variations in coolant saturationtemperature, local heat transfer rates, friction coefficients, and vaporquality along with complex conduction in a microprocessor package.

Various embodiments of the present invention can be directed to computerprocessing systems, computer-implemented methods, apparatus and/orcomputer program products that facilitate the efficient, effective, andautonomous (e.g., without direct human guidance) development oftwo-phase cooling architecture. The two-phase cooling architecture cancomprise an inlet and micro-channels. Coolant can be supplied to theinlet and distributed through the micro-channels across an area subjectto heat dissipating from a heat source (e.g., a processor). The coolantcan be supplied to the inlet as a liquid. As the coolant is distributedthrough the micro-channels, the coolant can absorb latent heat, changephase, and exit the micro-channels as a vapor. The inlet can be locatedat the center of the heated area, and the micro-channels can extendradially from the inlet to the edges of the heated area. Variousembodiments described herein can develop architecture defining the inletand micro-channels to meet operational constraints for a desired coolantand/or a desired heat source.

For example, one or more embodiments described herein can generate areduced physics model describing the structure of one or moremicro-channels of a cooling architecture based on one or moreoperational constraints and/or parameters. Also, various embodimentsdescribed herein can generate a full physics model describing thestructure of one or more inlets of the cooling architecture based on atleast on the reduced physics model. Additionally, one or moreembodiments described herein can alter constraints and/or parameters fora reduced physics model and/or a full physics model based on previouslygenerated models.

The computer processing systems, computer-implemented methods, apparatusand/or computer program products employ hardware and/or software tosolve problems that are highly technical in nature (e.g., modelingtwo-phase cooling architecture), that are not abstract and cannot beperformed as a set of mental acts by a human. Two-phase coolant flow isan extremely complex phenomena and computationally intensive to model.One or more embodiments of the present invention can facilitate rapidoptimization of cooling structure designs to achieve energy efficienttwo-phase cooling of micro-processors in a two dimensional (2D) as wellas in a 3D configuration. For example, a human, or even multiple humans,cannot efficiently, accurately, and effectively manually compute thevoluminous amounts of data describing a cooling architecture within areasonable amount of time. By employing computer generated models,various embodiments of the present invention can substantially reducedevelopment time restraints. Also, one or more of the models generatedby the computer processing systems, computer-implemented methods,apparatus and/or computer program products employ hardware and/orsoftware described herein can illustrate operational data (e.g., coolantflow and heat transfer) in a manner that is not readily obtainable bymere human computations. Further, by storing previously generatedmodels, including models that failed to meet operational constraints,one or more embodiments described herein can autonomously alterconstraints and/or parameters to render one or more new models feasible.

The present invention may be a system, a method, and/or a computerprogram product at any possible technical detail level of integration.The computer program product may include a computer readable storagemedium (or media) having computer readable program instructions thereonfor causing a processor to carry out aspects of the present invention.The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, configuration data for integrated circuitry, oreither source code or object code written in any combination of one ormore programming languages, including an object oriented programminglanguage such as Smalltalk, C++, or the like, and procedural programminglanguages, such as the “C” programming language or similar programminglanguages. The computer readable program instructions may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider). In some embodiments, electronic circuitry including,for example, programmable logic circuitry, field-programmable gatearrays (FPGA), or programmable logic arrays (PLA) may execute thecomputer readable program instructions by utilizing state information ofthe computer readable program instructions to personalize the electroniccircuitry, in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the blocks may occur out of theorder noted in the Figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

FIG. 1 illustrates a block diagram of an example, non-limiting system100 that can facilitate modeling a two-phase cooling structure inaccordance with one or more embodiments described herein. Aspects ofsystems (e.g., system 100 and the like), apparatuses or processes invarious embodiments of the present invention can constitute one or moremachine-executable components embodied within one or more machines,e.g., embodied in one or more computer readable mediums (or media)associated with one or more machines. Such components, when executed bythe one or more machines, e.g., computers, computing devices, virtualmachines, etc. can cause the machines to perform the operationsdescribed.

As shown in FIG. 1, the system 100 can comprise one or more servers 102,one or more networks 104, and one or more input devices 106. The server102 can comprise a design component 108. The design component 108 canfurther comprise reception component 110, case component 111 reducedphysics model component 112, full physics model component 114, and/orcombination component 115. Also, the server 102 can comprise orotherwise be associated with at least one memory 116. The server 102 canfurther comprise a system bus 118 that can couple to various componentssuch as, but not limited to, the design component 108 and associatedcomponents, memory 116 and/or a processor 120. While a server 102 isillustrated in FIG. 1, in other embodiments, multiple devices of varioustypes can be associated with or comprise the features shown in FIG. 1.

The one or more networks 104 can comprise wired and wireless networks,including, but not limited to, a cellular network, a wide area network(WAN) (e.g., the Internet) or a local area network (LAN). For example,the server 102 can communicate with the one or more input devices 106(and vice versa) using virtually any desired wired or wirelesstechnology including for example, but not limited to: cellular, WAN,wireless fidelity (Wi-Fi), Wi-Max, WLAN, Bluetooth technology, acombination thereof, and/or the like. Further, although in theembodiment shown the design component 108 can be provided on the one ormore servers 102, it should be appreciated that the architecture ofsystem 100 is not so limited. For example, the design component 108, orone or more components of design component 108, can be located atanother computer device, such as another server device, a client device,etc.

The one or more input devices 106 can be a computer device and/or ameans to enter data into a computer device. Example input devices 106include, but are not limited to: a personal computer, a keyboard, amouse, a computer tablet (e.g., a tablet comprising a processor andoperating system), a smartphone, and/or a website. The input device 106can be operably coupled to the server 102, and/or the input device 106can communicate with the server 102 via one or more networks 104.

In various embodiments, an entity can input design data into the inputdevice 106 regarding: one or more heat source profiles, one or moreoperational constraints, and/or one or more parameters of a coolingstructure. The one or more heat source profiles can comprise informationregarding a heat source (e.g., a microprocessor) that can supply theheat that the cooling architecture being modeled can be designed todissipate. For example, a heat source profile can indicate, but is notlimited to indicating: a type of heat source (e.g., a microprocessor),manufacturing data of the heat source (e.g., brand and/or model), aworkload power dissipation for the heat source, and/or a temperaturelimit of the heat source (e.g., a maximum temperature at which the heatsource can sustain functionality).

The one or more operational constraints can comprise informationregarding operational characteristics of the desired coolingarchitecture subject to modeling. An operational constraint can describedesired performance criteria to be exhibited by the cooling architecturesubject to modeling. Examples of one or more operational constraints caninclude, but are not limited to: coolant specification (e.g., type ofcoolant that can be utilized in the cooling architecture subject tomodeling), coolant characteristics (e.g., physical properties of thetype of coolant that can be utilized in the cooling architecture subjectto modeling), a pressure drop limit (e.g., a maximum change in pressurethat can be experienced in the cooling architecture subject tomodeling), a desired exit vapor quality (e.g., physical characteristicsof the vapor exiting the micro-channels of the cooling architecturesubject to modeling), and/or a coolant pumping power (e.g., the powerand/or pressure the coolant can be subject to in order to supply thecoolant to the inlet and/or micro-channels of the cooling architecturesubject to modeling).

The one or more parameters can comprise information regardingoperational and/or structural parameters of one or more coolingstructures in the architecture subject to modeling that can be changedin order to meet one or more operational constraints in relation to oneor more heat profiles. For example, the parameter can describe: a massflow rate of the coolant in the cooling architecture subject tomodeling, channel dimensions of the inlet and/or micro-channels of thecooling architecture subject to modeling, and/or layout of the inletand/or micro-channels of the cooling architecture subject to modeling.For instance, channel dimensions of the inlet and/or micro-channels ofthe cooling architecture subject to modeling can include, but are notlimited to: length, width, height, and/or taper angle of one or moreinlets; and/or length, width, height, and/or taper angle of one or moremicro-channels.

In another instance, layout of the inlet and/or micro-channels of thecooling architecture subject to modeling can include, but are notlimited to: the number of inlets in the cooling architecture subject tomodeling, the number of micro-channels in the cooling architecturesubject to modeling, the position of the one or more inlets in thecooling architecture subject to modeling (e.g., the inlets can belocated in a center position of the cooling architecture subject tomodeling), the position of the one or more micro-channels in the coolingarchitecture subject to modeling (e.g., the micro-channels can extendradially from the inlet to the perimeter of the heated area covered bythe cooling architecture subject to modeling), the orientation of one ormore micro-channels in the cooling architecture subject to modeling, thenumber of layers of the cooling architecture subject to modeling thatcomprise micro-channels, and/or which micro-channels are located onwhich layers of the cooling architecture subject to modeling.

The reception component 110 can receive the design data inputted intothe input device 106. The reception component 110 can be operablycoupled to the server 102, and/or the reception component 110 cancommunicate with the server 102 via one or more networks 104. Forexample, the reception component 110 can receive information regardingthe one or more heat source profiles, one or more operationalconstraints, and/or one or more variable parameters.

The case component 111 can define one or more cases based on at least aheat source profile and/or one or more parameters. The case component111 can define one or more cases based on a parameter (e.g., channeldimensions) of a cooling structure (e.g., micro-channels of a subjectcooling architecture). For example, the reception component 110 canreceive multiple parameters and the case component 111 can definemultiple cases, wherein each case can comprise a distinct parameterand/or a combination of the parameters. The one or more cases defined bythe case component 111 can be subject to modeling by the reduced physicsmodel component 112.

Further, the case component 111 can define one or more second casesbased on a second parameter (e.g., orifice length) of a second coolingstructure (e.g., an inlet of the subject cooling architecture). Forexample, the reception component 110 can receive multiple parametersthat include one or more second parameters, and the case component 111can define multiple second cases, wherein each second case can comprisea distinct second parameter and/or a combination of the secondparameters. The one or more second cases defined by the case component111 can be subject to modeling by the full physics model component 114.

The reduced physics model component 112 can generate a first modeldefining structural and/or operational characteristics of one or morefirst cooling structures (e.g., micro-channels) in the subject coolingarchitecture based on the data received by the reception component 110.The reduced physics model component 112 can be operably coupled to thereception component 110, and/or the reduced physics model component 112can communicate with the reception component 110 via one or morenetworks 104.

FIG. 2 illustrates a diagram of an example, non-limiting first model(e.g., a reduced physics model) that can be generated by the reducedphysics model component 112. Repetitive description of like elementsemployed in other embodiments described herein is omitted for sake ofbrevity. As shown in FIG. 2 the reduced physics model can be across-sectional averaged model in which the fluid domain can beexpressed in one dimension (1D) or 2D. Further the reduced physics modelcomponent 112 can illustrate heat transfer and/or fluid pressure of thecoolant as it is distributed from an inlet manifold 202 (e.g., an inletof a two-phase cooling architecture) and through one or more coolingchannels 204 (e.g., micro-channels of a of a two-phase coolingarchitecture).

For example, the reduced physics model component 112 can calculatetwo-phase friction pressure drop of the coolant within the coolingchannels of a subject cooling architecture by utilizing Equations 1-4.

$\begin{matrix}{\mspace{79mu}{{\Delta\; p_{fric}} = {\Phi^{2}\Delta\; p_{l}}}} & (1) \\{\mspace{79mu}{\Phi_{TT}^{2} = {1 + \frac{C}{X} + \frac{1}{X^{2}}}}} & (2) \\{X = \left\{ \begin{matrix}{\left( \frac{16}{0.046} \right)^{0.5}{{Re}_{v}^{- 0.4}\left( \frac{G_{l}}{G_{v}} \right)}^{0.5}\left( \frac{\rho_{v}}{\rho_{l}} \right)^{0.5}\left( \frac{\mu_{l}}{\mu_{v}} \right)^{0.5}} & {{Re}_{l} < {1000\mspace{14mu}{Re}_{v}} > 1000} \\{\left( \frac{1 - x}{x} \right)^{0.9}\left( \frac{\rho_{v}}{\rho_{l}} \right)^{0.5}\left( \frac{\mu_{l}}{\mu_{v}} \right)^{0.1}} & {{Re}_{l} > {1000\mspace{14mu}{Re}_{v}} > 1000}\end{matrix} \right.} & (3) \\{\mspace{79mu}{{Re}_{l} = {{\frac{G_{l}D_{h}}{\mu_{l}}\mspace{14mu}{Re}_{v}} = \frac{G_{v}D_{h}}{\mu_{v}}}}} & (4)\end{matrix}$Where “Δp” can represent an increment of pressure in kilo-pascals (kPa),subscript “fric” indicates frictional, “Φ” can represent a pressurecorrection factor, subscript “1” can indicate liquid phase of thecoolant, “X” can represent a Lockhart-Martinelli Parameter, “Re” canrepresent Reynolds Number, subscript “v” can indicate vapor phase of thecoolant, “G” can represent mass flux of the coolant in kilograms permeters squared times seconds (kg/m²s), “ρ” can represent density of thecoolant in kilograms per meter cubed (kg/m³), “μ” can representviscosity of the coolant in pascals times seconds (Pas), and “D” canrepresent hydraulic diameter. Also, “C” can be defined with respect tothe fluid behavior of the coolant, wherein a coolant with an Re of lessthan 1000 can be considered laminar, and a coolant with an Re of greaterthan 1000 can be considered turbulent. Below, Table 1 provides valuesfor “C” based on the fluid behavior of the coolant for each phase.

TABLE 1 Liquid Phase Vapor Phase “C” Value Turbulent Turbulent 20Laminar Turbulent 12 Turbulent Laminar 10 Laminar Laminar 5

In another example, the reduced physics model component 112 cancalculate two-phase heat transfer rates by utilizing Equations 5-6.

$\begin{matrix}{h_{pool} = {207\frac{\lambda_{l}}{d_{b}}\left( \frac{{qd}_{b}}{\lambda_{l}T_{l}} \right)^{0.745}\left( \frac{\rho_{v}}{\rho_{l}\;} \right)^{0.581}\Pr_{l}^{0.533}}} & (5) \\{d_{b} = {0.51\left\lbrack \frac{2\sigma}{g\left( {p_{l} - \rho_{v}} \right)} \right\rbrack}^{0.5}} & (6)\end{matrix}$Where “h” can represent a heat transfer coefficient in watts per metersquared times Kelvin (W/m²K), subscript “pool” can indicate pool boilingpoint, “λ” can indicate thermal conductivity in watts per meter timesKelvin (W/mK), subscript “b” can indicate a bubble, “T” can representtemperature of the coolant in Kelvin (K), “Pr” can represent the Prandtlnumber, “g” can represent a gravitational constant in meters per secondsquared (m/s²), and “σ” can represent surface tension of the coolant inNewton per meter (N/m).

Further, the reduced physics model component 112 can model thestructural features of the one or more cooling channels 204 in 3D. Forexample, the first model (e.g., reduced physics model) can illustrateand/or describe: the number of cooling channels 204 in the subjectmodel; the height, length, and/or width of the cooling channels 204 inthe subject model; the orientation and/or placement of the coolingchannels 204 in the subject model; the structure and/or position of oneor more pins located in the cooling channels 204 of the subject model;and/or the tapering angles of one or more cooling channels 204 in thesubject model.

In one or more embodiments, the reduced physics model component 112 cangenerate one or more first models based on the heat source profile andone or more parameters received by the reception component 110. Forexample, the one or more parameters can regard a cooling structure ofthe subject architecture (e.g., one or more cooling channels 204).Additionally, in various embodiments the reduced physics model component112 can generate the one or more first models based further on the oneor more operational constraints.

Further, the reduced physics model component 112 can determine thefeasibility of the generated first models based on the operationalconstraints received by the reception component 110. For example, thereduced physics model component 112 can determine the structural and/oroperational characteristics that are described by the receivedoperational constraints. The reduced physics model component 112 cancompare the determined structural and/or operational characteristics ofa subject first model with the operational constraints to determinewhether the first model complies with the operational constraints.Additionally, the reduced physics model component 112 can determinewhether the first model (e.g., reduced physics model) is capable offunctioning at the given parameters.

In addition, the reduced physics model component 112 can generate one ormore outputs from each of the first models that are determined feasible.The output can described desired conditions to maintain the feasibilityof the first model. Example outputs can include, but are not limited to:mass flow rate required for feasibility, expected pressure drop,expected exit vapor quality, and/or expected heat source temperature.For example, the reduced physics model component 112 can determine theexpected exit vapor quality by utilizing Equation 7.x=(φ+C _(p,liq)*(T _(sat,inlet) −T _(sat)))/h _(LV)  (7)Where “x” represents vapor quality (e.g., mass fraction of vapor), “ρ”can represent an additional variable in joules per kilogram (J/kg),subscript “liq” can indicate liquid phase, “*” represents themathematical symbol for convolution, subscript “sat, inlet” can indicatesaturation at inlet conditions, subscript “sat” can indicate localsaturation, and “h_(LV)” can represent the latent heat of vaporizationof the coolant.

The full physics model component 114 can generate a second model (e.g.,a full physics model) based on the first model and the one or moreoutputs generated by the reduced physics model component 112.Additionally, the full physics model component 114 can generate thesecond model based further on one or more parameters regarding a coolingstructure in the subject architecture (e.g., the inlet manifold 202).The second model (e.g., a full physics model) can define an architecturethat can achieve a flow distribution of a coolant. For example, the fullphysics model component 114 can generate a second model that illustratesand/or describes dimensions of the inlet manifold 202 (e.g., width,and/or length) and/or the dimensions (e.g., width, length and/or angle)of one or more inlet orifices 206 that allow fluid communication betweenthe inlet manifold 202 and the cooling channels 204. Example inletorifices can include, but are not limited to: straight slots, taperedslots, and/or pins.

FIG. 3 illustrates an example, non-limiting full physics model that canbe generated by the full physics model component 114. Repetitivedescription of like elements employed in other embodiments describedherein is omitted for sake of brevity. In various embodiments, the fullphysics model component 114 can utilize conservation equations forcontinuity, momentum, and/or energy for each phase and/or turbulence ofthe coolant.

For example, the full physics model component 114 can utilize Equation 8to calculate conservation of momentum.∇·(ρU⊗U)=−∇p+∇·(μ(∇U+(∇U)^(T)−⅔δ∇·U))+s _(M)  (8)Where “⊗” can be the mathematical symbol for tensor product, “U” canrepresent a velocity vector of the coolant in meters per second (m/s),and “S_(M)” can represent the momentum source term. The momentum sourceterm can enforce a pressure gradient profile for the coolant. Also, thefull physics model component 114 can utilize Equation 9 to calculatecontinuity.∇·(ρUH)=∇(λ∇T)+s _(E)  (9)

Further, the full physics model component 114 can utilize Equations 10and 11 to calculate conservation of energy.∇·(ρUH)=∇·(λ∇T)+s _(E)  (10)∇·(ρUφ)=∇·(ρA _(φ)∇φ)+S _(φ)  (11)Where “H” can represent the coolant specific enthalpy in joules perkilogram (J/kg), and “S_(E)” represents an energy source/sink term, “Aφ”can represent kinematic diffusion of the additional variable, and “Sφ”can represent the source term applied only at fluid-solid boundaries totransfer thermal information. Equation 11 can be utilized in conjunctionwith Equation 10 in order to track the coolant enthalpy evolution as thecoolant is distributed through the cooling architecture.

In various embodiments, the second model generated by the full physicsmodel component 114 can define the structural characteristics the inletmanifold 202 and the fluid communication between the inlet manifold 202and the cooling channels 204 of the subject cooling architecture. Also,the full physics model component 114 can determine the feasibility ofthe second model (e.g., full physics model) based on the one or moreoperational constraints received by the reception component 110. Forexample, the full physics model component 114 can determine thestructural and/or operational characteristics that are described by thereceived operational constraints. The full physics model component 114can compare the determined structural and/or operational characteristicsof a subject second model with the operational constraints to determinewhether the second model complies with the operational constraints.Additionally, the full physics model component 114 can determine whetherthe second model (e.g., full physics model) is capable of functioning atthe given parameters. Thus, the full physics model component 114 cangenerate a feasible full physics model that is: based on the reducedphysics model, meets the requirements indicated by the output of thereduced physics model, and meets the operational constraints.

In one or more embodiments, the combination component 115 can combine afeasible first model (e.g., reduced physics model) with a feasiblesecond model (e.g., full physics model) that was generated based on thefirst model in order to create a complete model that represents thetotal cooling architecture. Since the reduced physics model canrepresent feasible architecture of cooling channels 204 and the fullphysics model can represent feasible architecture of an inlet manifold202 and fluid communication between the inlet manifold 202 and thecooling channels 204, combination of a feasible reduced physics modeland a feasible full physics model can define architecture that canachieve a desired flow distribution of a coolant. By generating thefirst model and second model in stages, rather than generating a singlecomplete model all at once, one or more embodiments of the presentinvention can increase efficiency (e.g., reduce development time) ofgenerating the complete model at least because parameters that render acooling architecture infeasible can be readily identified in generationof the first model wherein minimal amount of resources (e.g., time) havebeen spent.

FIG. 4 illustrates a flow diagram of an example, non-limiting method 400that can be performed by the system 100. Repetitive description of likeelements employed in other embodiments described herein is omitted forsake of brevity. At 402 of method 400, design inputs (e.g., heat sourceprofiles, operational constraints, and/or parameters) can be received(e.g., via reception component 110). At 404 of method 400, cases can bedefined (e.g., via the case component 111) based on the design inputs.At 406 of method 400, a reduced physics model can be generated for adefined case (e.g., via the reduced physics model component 112). At 408of method 400, feasibility of the case can be determined with regard tothe generated reduced physics model (e.g., via the reduced physics modelcomponent 112). For example, the reduced physics model component 112 candetermine whether the reduced physics model can meet the operationalconstraints of the design input.

If it is determined (e.g., via the reduced physics model component 112)that the subject case is not feasible then the method 400 can proceed to410. At 410, a new case can be defined (e.g., via case component 111)based on the design inputs and the method 400 can proceed again from406. If it is determined (e.g., via the reduced physics model component112) that the subject case is feasible (e.g., remains functional whilemeeting the operational constraints), then the method 400 can proceed to412 and one or more outputs can be generated (e.g., via the reducedphysics model component 112) based on the reduced physics model.

At 414 of method 400, one or more second cases can be defined (e.g., viacase component 111) corresponding to the feasible case and based on oneor more of the parameters of the design input. At 416 of method 400, afull physics model can be generated for the second case (e.g., via thefull physics model component 114). At 418 of method 400, feasibility ofthe second case can be determined with regard to the generated fullphysics model (e.g., via the full physics model component 114). Forexample, the full physics model component 114 can determine whether thefull physics model can meet the operational constraints of the designinput while maintain functionality.

If it is determined (e.g., via the full physics model component 114)that the subject second case is not feasible then the method 400 canproceed to 420. At 420, a new second case can be defined (e.g., via casecomponent 111) and the method 400 can proceed again from 416. If it isdetermined (e.g., via the full physics model component 114) that thesubject second case is feasible (e.g., remains functional while meetingthe operational constraints), then the method 400 can proceed to 422. At422 the feasible reduced physics model and the feasible full physicsmodel generated based on the reduced physics model can be combined(e.g., via combination component 115) to generate a complete model thatcan represent the architect that can achieve a desired coolantdistribution.

At 424 it can be determined whether a full physics model has beengenerated for all the defined second cases. If it is determined that afull physics model has not been generated for all the defined secondcases, then the method 400 can proceed to 416 and can generate a fullphysics model (e.g., via the full physics model component 114) for oneof the defined second cases that has not been subjected to a fullphysics model. If it is determined that a full physics model has beengenerated for all the defined second cases, then the method 400 can becomplete.

FIG. 5 illustrates a block diagram on another example, non-limitingsystem 100 that can further comprise an alteration component 502 and amodel database 504. Repetitive description of like elements employed inother embodiments described herein is omitted for sake of brevity. Thealteration component 502 can be operably coupled to the reduced physicsmodel component 112 and/or the full physics model component 114, and/orthe alteration component 502 can communicate with the reduced physicsmodel component 112 and/or the full physics model component 114 via oneor more networks 104.

In one or more embodiments, the alteration component 502 can utilizeartificial intelligence (AI) techniques (e.g., neural networks, geneticalgorithms, and/or reinforcement learning) to generate one or morealterations to one or more parameters. By generating one or morealterations, the alteration component 502 can define a new case orsecond case in response to the subject case or second case beingdetermined infeasible (e.g., via the reduced physics model component 112and/or the full physics model component 114). The model database 504 canbe stored in the memory 116 and can comprise each first model (e.g.,reduced physics model) and/or second model (e.g., full physics model)generated by the reduced physics model component 112 and/or the fullphysics model component 114 (despite whether the subject model wasdetermined feasible or not). The alteration component 502 can learn fromthe one or more models comprising the model database 504 to makealterations to a subject case (e.g., to one or more parameters of thesubject case) that is determined infeasible, wherein the alterationcomponent 502 can implement the alterations to define a new case and/ora new second case.

For example, the alteration component 502 can analyze one or more modelsfrom the model database 504 to determine relationships betweencharacteristics of the models and the subject parameters of the models.For instance, in regards to case that was determined infeasible based onits reduced physics model, the alteration component 502 can suggestalterations to one or more dimension and/or layout of the coolingchannels 204. In another instance, in regards to second case that wasdetermined infeasible based on its full physics model, the alterationcomponent 502 can suggest alterations to one or more dimension and/orlayout of the inlet manifold 202. From the determined relationships, thealteration component 502 can generate alterations to the parameters of asubject case to define a new case. Example, alterations that can begenerated by the alteration component 502 can include, but are notlimited to: altering the number of cooling channels 204, altering thedimensions of one or more cooling channels 204 (e.g., height, length,and/or width), altering the orientation of one or more cooling channels204, altering the number of inlet manifolds 202, altering the dimensionsof the inlet manifold 202 (e.g., width and/or length), altering the typeand/or number of inlet orifice 206 that facilitates fluid communicationbetween the inlet manifold 202 and the one or more cooling channels 204,altering the number of layers in the cooling architecture that comprisecooling channels 204, altering the expansion of the cooling channels204, and/or altering the number of pins included in the cooling channels204.

FIG. 6 illustrates a flow diagram of an example, non-limiting method 600that can be performed by the system 100. Repetitive description of likeelements employed in other embodiments described herein is omitted forsake of brevity. At 602 of method 600, design inputs (e.g., heat sourceprofiles, operational constraints, and/or parameters) can be received(e.g., by reception component 110). At 604 of method 600, cases can bedefined based on the design inputs (e.g., via case component 111). At606 of method 600, a reduced physics model can be generated for adefined case (e.g., via the reduced physics model component 112). At 608of method 600, feasibility of the case can be determined with regard tothe generated reduced physics model (e.g., via the reduced physics modelcomponent 112). For example, the reduced physics model component 112 candetermine whether the reduced physics model can meet the operationalconstraints of the design input.

If it is determined (e.g., via the reduced physics model component 112)that the subject case is not feasible then the method 600 can proceed to610. At 610, a new case can be defined based on one or more alterationslearned from one or more past models (e.g., via the alteration component502) and the method 600 can proceed again from 606. If it is determined(e.g., via the reduced physics model component 112) that the subjectcase is feasible (e.g., remains functional while meeting the operationalconstraints), then the method 600 can proceed to 612 and one or moreoutputs can be generated (e.g., via the reduced physics model component112) based on the reduced physics model.

At 614 of method 600, one or more second cases can be defined (e.g., viathe case component 111) corresponding to the feasible case and based onone or more of the parameters of the design input. At 616 of method 600,a full physics model can be generated for the second case (e.g., via thefull physics model component 114). At 618 of method 600, feasibility ofthe second case can be determined with regard to the generated fullphysics model (e.g., via the full physics model component 114). Forexample, the full physics model component 114 can determine whether thefull physics model can meet the operational constraints of the designinput while maintain functionality.

If it is determined (e.g., via the full physics model component 114)that the subject second case is not feasible then the method 600 canproceed to 620. At 620, a new second case can be defined based on one ormore alterations learned from one or more past models (e.g., via thealteration component 502) and the method 600 can proceed again from 616.If it is determined (e.g., via the full physics model component 114)that the subject second case is feasible (e.g., remains functional whilemeeting the operational constraints), then the method 600 can proceed to622. At 622 the feasible reduced physics model and the feasible fullphysics model generated based on the reduced physics model can becombined (e.g., via combination component 115) to generate a completemodel that can represent the architect that can achieve a desiredcoolant distribution.

At 624, it can be determined whether a full physics model has beengenerated for all the defined second cases. If it is determined that afull physics model has not been generated for all the defined secondcases, then the method 600 can proceed to 616 and can generate a fullphysics model (e.g., via the full physics model component 114) for oneof the defined second cases that has not been subjected to a fullphysics model. If it is determined that a full physics model has beengenerated for all the defined second cases, then the method 600 can becomplete.

FIG. 7 illustrates a block diagram on another example, non-limitingsystem 100 that can further comprise a display component 702. Repetitivedescription of like elements employed in other embodiments describedherein is omitted for sake of brevity. The display component 702 can beoperably coupled to the design component 108, and the design component's108 associated components, and/or the display component 702 cancommunicate with the design component 108, and the design component's108 associated components, via one or more networks 104.

In one or more embodiments, the display component 702 can display one ormore of the first models (e.g., reduced physics models) and/or one ormore of the second models (e.g., full physics models) on a screen. Thescreen can be operably coupled to the display component 702, and/or thescreen can communicate with the display component 702 via one or morenetworks 104. The display component 702 can display the first and/orsecond models as digital images illustrating 3D or 2D views.

In various embodiments, the display component 702 can further displayperformance characteristics regarding a subject model (e.g., a reducedphysics model, a full physics model, and/or a complete model) that werereceived by the reception component 110, generated by the reducedphysics model component 112, and/or generated by the full physics modelcomponent 114. The performance characteristics can include, but are notlimited to: information regarding a heat source profile, informationregarding one or more operational constraints, information regarding oneor more parameters, information regarding one or more structuralcharacteristics of the subject model, and/or one or more coolantdistribution characteristics achieved by the subject model. Also, theperformance characteristics can be displayed in an easily readableformat such as, but not limited to: a list, a table, a chart, and/or agraph.

Below, Table 2 provides an example, non-limiting, performancecharacteristic table comprising information that can be received and/orgenerated by the design component 108 and can be displayed by thedisplay component 702.

TABLE 2 Coolant: R1234ze Liquid ρ_(l) = 11464 kg/m³ C_(pl) = 1402.9 J/kg· K μ_(l) = 1.88e⁻⁴ Pa · s λ_(l) = 0.0725 W/m · K Phase: Vapor ρ_(v) =30.52 kg/m3 C_(pv) = 998.57 J/kg · K μ_(v) = 1.24e⁻⁵ Pa · s λ_(l) =0.014 W/m · K Phase: Latent Heat: H_(lv) = 163060 J/kg SaturationTemperature${T_{sat}\lbrack C\rbrack} = {{55.8426*\left( \frac{P_{abs}}{1\lbrack{MPa}\rbrack} \right)^{3}} - {137.2327*\left( \frac{P_{abs}}{1\lbrack{MPa}\rbrack} \right)^{2}} + {161.6659*\left( \frac{P_{abs}}{1\lbrack{MPa}\rbrack} \right)} - 28.39}$Chip: Silicon Chip ρ = 2230 kg/m³ C_(p) = 703 J/kg · K λ = 149 W/m · KProperties: Cover Plate: Glass Cover Plate ρ = 2230 kg/m³ C_(p) = 753.12J/kg · K λ = 1.1 W/m · K Properties:Where “coolant” can refer to the type of coolant utilized in the coolingarchitecture represented by the subject model; “liquid phase” can referto characteristics of the coolant while the coolant is in a liquidphase; “vapor phase” can refer to characteristics of the coolant whilethe coolant is in a vapor phase; “latent heat” can refer to the latentheat of the coolant; “saturation temperature can refer to the saturationtemperature of the coolant, wherein subscript “abs” indicates absolute;“MPa” can refer to mega pascals; “chip” can refer to the type of chipwhich the cooling architect will be positioned upon; “chip properties”can refer to properties of the chip; “cover plate” can refer the type ofplate that can cover the top most layer of the cooling architecture thatcomprises cooling channels 204; and “cover plate properties” can referto properties achieved by the cover plate.

FIG. 8 illustrates a flow diagram of an example, non-limitingcomputer-implemented method 800 that can facilitate modeling a two phasecooling structure in accordance with one or more embodiments describedherein. Repetitive description of like elements employed in otherembodiments described herein is omitted for sake of brevity. At 802, themethod 800 can comprise generating, by a system 100 operatively coupledto a processor 120, a reduced physics model based on a profile of a heatsource and a parameter of a cooling structure. The reduced physics modelcan provide an output. At 804, the method 800 can also comprisegenerating, by the system 100, a full physics model based on the output.Further, at 806 the method 800 can comprise combining, by the system100, the reduced physics model and the full physics model to define anarchitecture that can achieve a flow distribution of a coolant.

FIG. 9 illustrates a flow diagram of another example, non-limitingcomputer-implemented method 900 that can facilitate modeling a two phasecooling structure in accordance with one or more embodiments describedherein. Repetitive description of like elements employed in otherembodiments described herein is omitted for sake of brevity. At 902, themethod 900 can comprise generating (e.g., via reduced physics modelcomponent 112), by a system 100 operatively coupled to a processor 120,a reduced physics model based on a profile of a heat source and aparameter of a cooling structure (e.g., one or more cooling channels204). The reduced physics model can provide an output. At 904, themethod 900 can comprise determining (e.g., via reduced physics modelcomponent 112), by the system 100, whether the reduced physics modulecomplies with an operational constraint. At 906, the method 900 cancomprise altering (e.g., via alteration component 502), by the system100, the parameter based on a determination (e.g., via reduced physicsmodel component 112) that the reduction physics model does not complywith the operational constraint. At 908, the method 900 can furthercomprise generating (e.g., via full physics model component 114), by thesystem 100, a full physics model based on the output and a secondparameter of a second cooling structure (e.g., inlet manifold 202).Further, at 910 the method 900 can comprise determining (e.g., via fullphysics model component 114), by the system 100, whether the fullphysics model complies with an operational constraint. At 912, themethod 900 can comprise altering (e.g., via alteration component 502),by the system 100, the second parameter based on a determination thatthe full physics model does not comply with the operations constraint.Moreover, at 914 the method 900 can comprise combining (e.g., viacombination component 115), by the system 100, the reduced physics modeland the full physics model to define an architecture that can achieve aflow distribution of a coolant based on a determination (e.g., via fullphysics model component 114) that the full physics model complies withthe operational constraint.

In order to provide a context for the various aspects of the disclosedsubject matter, FIG. 10 as well as the following discussion are intendedto provide a general description of a suitable environment in which thevarious aspects of the disclosed subject matter can be implemented. FIG.10 illustrates a block diagram of an example, non-limiting operatingenvironment in which one or more embodiments described herein can befacilitated. Repetitive description of like elements employed in otherembodiments described herein is omitted for sake of brevity. Withreference to FIG. 10, a suitable operating environment 1000 forimplementing various aspects of this disclosure can include a computer1012. The computer 1012 can also include a processing unit 1014, asystem memory 1016, and a system bus 1018. The system bus 1018 canoperably couple system components including, but not limited to, thesystem memory 1016 to the processing unit 1014. The processing unit 1014can be any of various available processors. Dual microprocessors andother multiprocessor architectures also can be employed as theprocessing unit 1014. The system bus 1018 can be any of several types ofbus structures including the memory bus or memory controller, aperipheral bus or external bus, and/or a local bus using any variety ofavailable bus architectures including, but not limited to, IndustrialStandard Architecture (ISA), Micro-Channel Architecture (MSA), ExtendedISA (EISA), Intelligent Drive Electronics (IDE), VESA Local Bus (VLB),Peripheral Component Interconnect (PCI), Card Bus, Universal Serial Bus(USB), Advanced Graphics Port (AGP), Firewire, and Small ComputerSystems Interface (SCSI). The system memory 1016 can also includevolatile memory 1020 and nonvolatile memory 1022. The basic input/outputsystem (BIOS), containing the basic routines to transfer informationbetween elements within the computer 1012, such as during start-up, canbe stored in nonvolatile memory 1022. By way of illustration, and notlimitation, nonvolatile memory 1022 can include read only memory (ROM),programmable ROM (PROM), electrically programmable ROM (EPROM),electrically erasable programmable ROM (EEPROM), flash memory, ornonvolatile random access memory (RAM) (e.g., ferroelectric RAM (FeRAM).Volatile memory 1020 can also include random access memory (RAM), whichacts as external cache memory. By way of illustration and notlimitation, RAM is available in many forms such as static RAM (SRAM),dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM(DDR SDRAM), enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), directRambus RAM (DRRAM), direct Rambus dynamic RAM (DRDRAM), and Rambusdynamic RAM.

Computer 1012 can also include removable/non-removable,volatile/non-volatile computer storage media. FIG. 10 illustrates, forexample, a disk storage 1024. Disk storage 1024 can also include, but isnot limited to, devices like a magnetic disk drive, floppy disk drive,tape drive, Jaz drive, Zip drive, LS-100 drive, flash memory card, ormemory stick. The disk storage 1024 also can include storage mediaseparately or in combination with other storage media including, but notlimited to, an optical disk drive such as a compact disk ROM device(CD-ROM), CD recordable drive (CD-R Drive), CD rewritable drive (CD-RWDrive) or a digital versatile disk ROM drive (DVD-ROM). To facilitateconnection of the disk storage 1024 to the system bus 1018, a removableor non-removable interface can be used, such as interface 1026. FIG. 10also depicts software that can act as an intermediary between users andthe basic computer resources described in the suitable operatingenvironment 1000. Such software can also include, for example, anoperating system 1028. Operating system 1028, which can be stored ondisk storage 1024, acts to control and allocate resources of thecomputer 1012. System applications 1030 can take advantage of themanagement of resources by operating system 1028 through program modules1032 and program data 1034, e.g., stored either in system memory 1016 oron disk storage 1024. It is to be appreciated that this disclosure canbe implemented with various operating systems or combinations ofoperating systems. A user enters commands or information into thecomputer 1012 through one or more input devices 1036. Input devices 1036can include, but are not limited to, a pointing device such as a mouse,trackball, stylus, touch pad, keyboard, microphone, joystick, game pad,satellite dish, scanner, TV tuner card, digital camera, digital videocamera, web camera, and the like. These and other input devices canconnect to the processing unit 1014 through the system bus 1018 via oneor more interface ports 1038. The one or more Interface ports 1038 caninclude, for example, a serial port, a parallel port, a game port, and auniversal serial bus (USB). One or more output devices 1040 can use someof the same type of ports as input device 1036. Thus, for example, a USBport can be used to provide input to computer 1012, and to outputinformation from computer 1012 to an output device 1040. Output adapter1042 can be provided to illustrate that there are some output devices1040 like monitors, speakers, and printers, among other output devices1040, which require special adapters. The output adapters 1042 caninclude, by way of illustration and not limitation, video and soundcards that provide a means of connection between the output device 1040and the system bus 1018. It should be noted that other devices and/orsystems of devices provide both input and output capabilities such asone or more remote computers 1044.

Computer 1012 can operate in a networked environment using logicalconnections to one or more remote computers, such as remote computer1044. The remote computer 1044 can be a computer, a server, a router, anetwork PC, a workstation, a microprocessor based appliance, a peerdevice or other common network node and the like, and typically can alsoinclude many or all of the elements described relative to computer 1012.For purposes of brevity, only a memory storage device 1046 isillustrated with remote computer 1044. Remote computer 1044 can belogically connected to computer 1012 through a network interface 1048and then physically connected via communication connection 1050.Further, operation can be distributed across multiple (local and remote)systems. Network interface 1048 can encompass wire and/or wirelesscommunication networks such as local-area networks (LAN), wide-areanetworks (WAN), cellular networks, etc. LAN technologies include FiberDistributed Data Interface (FDDI), Copper Distributed Data Interface(CDDI), Ethernet, Token Ring and the like. WAN technologies include, butare not limited to, point-to-point links, circuit switching networkslike Integrated Services Digital Networks (ISDN) and variations thereon,packet switching networks, and Digital Subscriber Lines (DSL). One ormore communication connections 1050 refers to the hardware/softwareemployed to connect the network interface 1048 to the system bus 1018.While communication connection 1050 is shown for illustrative clarityinside computer 1012, it can also be external to computer 1012. Thehardware/software for connection to the network interface 1048 can alsoinclude, for exemplary purposes only, internal and external technologiessuch as, modems including regular telephone grade modems, cable modemsand DSL modems, ISDN adapters, and Ethernet cards.

Embodiments of the present invention can be a system, a method, anapparatus and/or a computer program product at any possible technicaldetail level of integration. The computer program product can include acomputer readable storage medium (or media) having computer readableprogram instructions thereon for causing a processor to carry outaspects of the present invention. The computer readable storage mediumcan be a tangible device that can retain and store instructions for useby an instruction execution device. The computer readable storage mediumcan be, for example, but is not limited to, an electronic storagedevice, a magnetic storage device, an optical storage device, anelectromagnetic storage device, a semiconductor storage device, or anysuitable combination of the foregoing. A non-exhaustive list of morespecific examples of the computer readable storage medium can alsoinclude the following: a portable computer diskette, a hard disk, arandom access memory (RAM), a read-only memory (ROM), an erasableprogrammable read-only memory (EPROM or Flash memory), a static randomaccess memory (SRAM), a portable compact disc read-only memory (CD-ROM),a digital versatile disk (DVD), a memory stick, a floppy disk, amechanically encoded device such as punch-cards or raised structures ina groove having instructions recorded thereon, and any suitablecombination of the foregoing. A computer readable storage medium, asused herein, is not to be construed as being transitory signals per se,such as radio waves or other freely propagating electromagnetic waves,electromagnetic waves propagating through a waveguide or othertransmission media (e.g., light pulses passing through a fiber-opticcable), or electrical signals transmitted through a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network can includecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device. Computer readable programinstructions for carrying out operations of various aspects of thepresent invention can be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, configuration data for integrated circuitry, oreither source code or object code written in any combination of one ormore programming languages, including an object oriented programminglanguage such as Smalltalk, C++, or the like, and procedural programminglanguages, such as the “C” programming language or similar programminglanguages. The computer readable program instructions can executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer can be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection can be made to anexternal computer (for example, through the Internet using an InternetService Provider). In some embodiments, electronic circuitry including,for example, programmable logic circuitry, field-programmable gatearrays (FPGA), or programmable logic arrays (PLA) can execute thecomputer readable program instructions by utilizing state information ofthe computer readable program instructions to customize the electroniccircuitry, in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions. These computer readable programinstructions can be provided to a processor of a general purposecomputer, special purpose computer, or other programmable dataprocessing apparatus to produce a machine, such that the instructions,which execute via the processor of the computer or other programmabledata processing apparatus, create means for implementing thefunctions/acts specified in the flowchart and/or block diagram block orblocks. These computer readable program instructions can also be storedin a computer readable storage medium that can direct a computer, aprogrammable data processing apparatus, and/or other devices to functionin a particular manner, such that the computer readable storage mediumhaving instructions stored therein includes an article of manufactureincluding instructions which implement aspects of the function/actspecified in the flowchart and/or block diagram block or blocks. Thecomputer readable program instructions can also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational acts to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams can represent a module, segment, or portionof instructions, which includes one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the blocks can occur out of theorder noted in the Figures. For example, two blocks shown in successioncan, in fact, be executed substantially concurrently, or the blocks cansometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

While the subject matter has been described above in the general contextof computer-executable instructions of a computer program product thatruns on a computer and/or computers, those skilled in the art willrecognize that this disclosure also can or can be implemented incombination with other program modules. Generally, program modulesinclude routines, programs, components, data structures, etc. thatperform particular tasks and/or implement particular abstract datatypes. Moreover, those skilled in the art will appreciate that theinventive computer-implemented methods can be practiced with othercomputer system configurations, including single-processor ormultiprocessor computer systems, mini-computing devices, mainframecomputers, as well as computers, hand-held computing devices (e.g., PDA,phone), microprocessor-based or programmable consumer or industrialelectronics, and the like. The illustrated aspects can also be practicedin distributed computing environments where tasks are performed byremote processing devices that are linked through a communicationsnetwork. However, some, if not all aspects of this disclosure can bepracticed on stand-alone computers. In a distributed computingenvironment, program modules can be located in both local and remotememory storage devices.

As used in this application, the terms “component,” “system,”“platform,” “interface,” and the like, can refer to and/or can include acomputer-related entity or an entity related to an operational machinewith one or more specific functionalities. The entities disclosed hereincan be either hardware, a combination of hardware and software,software, or software in execution. For example, a component can be, butis not limited to being, a process running on a processor, a processor,an object, an executable, a thread of execution, a program, and/or acomputer. By way of illustration, both an application running on aserver and the server can be a component. One or more components canreside within a process and/or thread of execution and a component canbe localized on one computer and/or distributed between two or morecomputers. In another example, respective components can execute fromvarious computer readable media having various data structures storedthereon. The components can communicate via local and/or remoteprocesses such as in accordance with a signal having one or more datapackets (e.g., data from one component interacting with anothercomponent in a local system, distributed system, and/or across a networksuch as the Internet with other systems via the signal). As anotherexample, a component can be an apparatus with specific functionalityprovided by mechanical parts operated by electric or electroniccircuitry, which is operated by a software or firmware applicationexecuted by a processor. In such a case, the processor can be internalor external to the apparatus and can execute at least a part of thesoftware or firmware application. As yet another example, a componentcan be an apparatus that provides specific functionality throughelectronic components without mechanical parts, wherein the electroniccomponents can include a processor or other means to execute software orfirmware that confers at least in part the functionality of theelectronic components. In an aspect, a component can emulate anelectronic component via a virtual machine, e.g., within a cloudcomputing system.

In addition, the term “or” is intended to mean an inclusive “or” ratherthan an exclusive “or.” That is, unless specified otherwise, or clearfrom context, “X employs A or B” is intended to mean any of the naturalinclusive permutations. That is, if X employs A; X employs B; or Xemploys both A and B, then “X employs A or B” is satisfied under any ofthe foregoing instances. Moreover, articles “a” and “an” as used in thesubject specification and annexed drawings should generally be construedto mean “one or more” unless specified otherwise or clear from contextto be directed to a singular form. As used herein, the terms “example”and/or “exemplary” are utilized to mean serving as an example, instance,or illustration. For the avoidance of doubt, the subject matterdisclosed herein is not limited by such examples. In addition, anyaspect or design described herein as an “example” and/or “exemplary” isnot necessarily to be construed as preferred or advantageous over otheraspects or designs, nor is it meant to preclude equivalent exemplarystructures and techniques known to those of ordinary skill in the art.

As it is employed in the subject specification, the term “processor” canrefer to substantially any computing processing unit or deviceincluding, but not limited to, single-core processors; single-processorswith software multithread execution capability; multi-core processors;multi-core processors with software multithread execution capability;multi-core processors with hardware multithread technology; parallelplatforms; and parallel platforms with distributed shared memory.Additionally, a processor can refer to an integrated circuit, anapplication specific integrated circuit (ASIC), a digital signalprocessor (DSP), a field programmable gate array (FPGA), a programmablelogic controller (PLC), a complex programmable logic device (CPLD), adiscrete gate or transistor logic, discrete hardware components, or anycombination thereof designed to perform the functions described herein.Further, processors can exploit nano-scale architectures such as, butnot limited to, molecular and quantum-dot based transistors, switchesand gates, in order to optimize space usage or enhance performance ofuser equipment. A processor can also be implemented as a combination ofcomputing processing units. In this disclosure, terms such as “store,”“storage,” “data store,” data storage,” “database,” and substantiallyany other information storage component relevant to operation andfunctionality of a component are utilized to refer to “memorycomponents,” entities embodied in a “memory,” or components including amemory. It is to be appreciated that memory and/or memory componentsdescribed herein can be either volatile memory or nonvolatile memory, orcan include both volatile and nonvolatile memory. By way ofillustration, and not limitation, nonvolatile memory can include readonly memory (ROM), programmable ROM (PROM), electrically programmableROM (EPROM), electrically erasable ROM (EEPROM), flash memory, ornonvolatile random access memory (RAM) (e.g., ferroelectric RAM (FeRAM).Volatile memory can include RAM, which can act as external cache memory,for example. By way of illustration and not limitation, RAM is availablein many forms such as synchronous RAM (SRAM), dynamic RAM (DRAM),synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhancedSDRAM (ESDRAM), Synchlink DRAM (SLDRAM), direct Rambus RAM (DRRAM),direct Rambus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM).Additionally, the disclosed memory components of systems orcomputer-implemented methods herein are intended to include, withoutbeing limited to including, these and any other suitable types ofmemory.

What has been described above include mere examples of systems, computerprogram products and computer-implemented methods. It is, of course, notpossible to describe every conceivable combination of components,products and/or computer-implemented methods for purposes of describingthis disclosure, but one of ordinary skill in the art can recognize thatmany further combinations and permutations of this disclosure arepossible. Furthermore, to the extent that the terms “includes,” “has,”“possesses,” and the like are used in the detailed description, claims,appendices and drawings such terms are intended to be inclusive in amanner similar to the term “comprising” as “comprising” is interpretedwhen employed as a transitional word in a claim. The descriptions of thevarious embodiments have been presented for purposes of illustration,but are not intended to be exhaustive or limited to the embodimentsdisclosed. Many modifications and variations will be apparent to thoseof ordinary skill in the art without departing from the scope and spiritof the described embodiments. The terminology used herein was chosen tobest explain the principles of the embodiments, the practicalapplication or technical improvement over technologies found in themarketplace, or to enable others of ordinary skill in the art tounderstand the embodiments disclosed herein.

What is claimed is:
 1. A computer-implemented method, comprising:iteratively performing, by a system operatively coupled to a processor,a first set of operations until a reduced physics model is determined tobe feasible, where the first set of operations comprise: generating thereduced physics model based on a profile of a heat source, one or moreoperational constraints for cooling the heat source, and one or moreparameters related to designing a two-phase cooling structure that isthree-dimensional, wherein the reduced physics model defines anarchitecture of cooling channels of the two-phase cooling structureusing a first subset of the one or more parameters, and the reducedphysics model models a fluid domain of the cooling channels in onedimension or two dimensions, and models structural features of thecooling channels in three dimensions, determining whether the reducedphysics model is feasible based on the one or more operationalconstraints, in response to a determining that the reduced physics modelis not feasible, altering at least one parameter of the first subset,and in response to determining that the reduced physics model isfeasible, generating at least one output that maintains a definedthermal performance of the reduced physics model with respect to the oneor more operational constraints, and the at least one output is selectedfrom a group consisting of a mass flow rate, a pressure drop, and anexit vapor quality, and; iteratively performing, by the system, a secondset of operations until a full physics model is determined to befeasible, where the second set of operations comprise: generating thefull physics model based on the at least one output and a second subsetof the one or more parameters, wherein the full physics model defines anarchitecture of an inlet manifold of the two-phase cooling structure,and models fluid communication of a coolant between the inlet manifoldand the cooling channels, determining whether the full physics model isfeasible based on whether the full physics model satisfies the at leastone output of the reduced physics model and the one or more operationalconstraints, in response to a determination that the full physics modelis not feasible, altering at least one parameter of the second subset,and in response to determining that the full physics model is feasible,combining the reduced physics model and the full physics model to definethe two phase cooling structure for achieving the defined thermalperformance.
 2. The computer-implemented method of claim 1, wherein theat least one output comprises at least two outputs selected from thegroup consisting of the mass flow rate, the pressure drop, and the exitvapor quality.
 3. The computer-implemented method of claim 1, whereinthe heat source is a three-dimensional stacked integrated circuitsmicroprocessor.
 4. The computer-implemented method of claim 1, furthercomprising generating, by the system, a display showing a performancecharacteristic of the two phase cooling structure.
 5. Thecomputer-implemented method of claim 1, wherein the at least one outputcomprises the mass flow rate, the pressure drop, and the exit vaporquality.
 6. The computer-implemented method of claim 1, wherein thecoolant undergoes a phase change during the fluid communication.
 7. Thecomputer-implemented method of claim 1, wherein the full physics modelcomponent enforces a pressure gradient profile for the coolant duringgeneration of the full physics model.
 8. The computer-implemented methodof claim 1, wherein the second set of operations further comprisestracking, by the system, coolant enthalpy evolution as the coolant isdistributed through the two-phase cooling structure.
 9. Thecomputer-implemented method of claim 1, wherein the two phase coolingstructure for achieving the defined thermal performance achieves adefined flow distribution of the coolant through the two phase coolingstructure.
 10. The computer-implemented method of claim 1, wherein thefirst set of operations further comprises determining, by the system, atwo-phase friction pressure drop of the coolant within the coolingchannels.